Type of Document Master's Thesis Author Hession, William Culliton URN etd-10132010-020034 Title Pre-mining hydrologic analysis using modeling and geographic information system technology Degree Master of Science Department Agricultural Engineering Advisory Committee
Advisor Name Title Shanholtz, Vernon O. Committee Chair Dillaha, Theo A. III Committee Member Mostaghimi, Saied Committee Member Ross, Burton Blake Committee Member Keywords
- Strip mining
Date of Defense 1988-06-05 Availability restricted AbstractSurface mining activities are known to affect the quantity and quality of stormwater runoff. This can create flooding and water quality degradation of receiving streams. The Surface Mining Control and Reclamation Act (SMCRA) of 1977 provides regulations intended to produce environmentally acceptable results from mining operations.
The SMCRA requires that extensive pre-mining monitoring be carried out to assist in determining the probable hydrologic consequences (PHC) of mining. The Finite Element Storm Hydrograph Model (FESHM) was used to demonstrate the utility of hydrologic modeling concepts in simulating runoff volumes and peak flows. Guidelines were proposed for using this methodology to simulate selected pre-mining hydrologic conditions.
The use of geographic information system (GIS) technology as a tool for improving data management and modeling efficiency was demonstrated. The required input watershed characteristics were digitized, stored, and manipulated using a computerized GIS. Appropriate software was developed to integrate the GIS with FESHM.
The ability of FESHM to simulate runoff events in an ungaged context was evaluated using an experimental watershed. First, simulations were conducted using two separate data bases, "lumped" and "detailed", in order to evaluate the effect of limited data availability, as expected in mining regions, on FESHM's predictive ability. The "lumped" data base produced better simulation results, however, more thorough and detailed research is needed to determine the level of data resolution necessary for a given level of simulation accuracy. Next., significant runoff events from 17-years of the historical record were simulated using data from the "lumped" data base. Statistical analyses were used to make judgments on parameter estimation and model usage. Regression methodology was used to assess expected error and model bias. Simulation bias was found to be related to the input rainfall intensity levels. The results suggest that either spatial variability or parameter values were not adequately defined and that some form of calibration is needed.
Two additional drainage basins were used to evaluate FESHM's predictive capabilities in situations considered representative of mining regions. The results indicated that more thorough investigations of watershed characteristics must be made, that calibration procedures should be performed for each watershed, and that FESHM does not adequately model the physical processes involved in forest hydrology.
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